2021
Artificial intelligence applied to breast pathology
Yousif M, van Diest PJ, Laurinavicius A, Rimm D, van der Laak J, Madabhushi A, Schnitt S, Pantanowitz L. Artificial intelligence applied to breast pathology. Virchows Archiv 2021, 480: 191-209. PMID: 34791536, DOI: 10.1007/s00428-021-03213-3.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceBreastBreast NeoplasmsFemaleHumansMachine LearningNeural Networks, ComputerConceptsArtificial intelligenceApplication of AIComplex artificial intelligenceDevelopment of algorithmsComputer visionDeep learningMachine learningMitosis detectionDigital pathologyNeural networkDigital dataHistology imagesTissue segmentationField of pathologyImage analysisIntelligencePromising resultsTaskLearningImagesSegmentationBreast pathologyComputerAlgorithmNetworkAn independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy
Perincheri S, Levi AW, Celli R, Gershkovich P, Rimm D, Morrow JS, Rothrock B, Raciti P, Klimstra D, Sinard J. An independent assessment of an artificial intelligence system for prostate cancer detection shows strong diagnostic accuracy. Modern Pathology 2021, 34: 1588-1595. PMID: 33782551, PMCID: PMC8295034, DOI: 10.1038/s41379-021-00794-x.Peer-Reviewed Original ResearchConceptsMemorial Sloan-Kettering Cancer CenterCore biopsyPredictive valueDiagnostic accuracyProstate core needle biopsiesCore needle biopsySurgical pathology practiceNegative predictive valueProstate core biopsiesPositive predictive valueProstate cancer detectionStrong diagnostic accuracyPoor quality scansCancer detectionCancer CenterProstate biopsyLeading causeNeedle biopsyTransrectal approachProstate cancerProstatic adenocarcinomaProstate carcinomaBiopsyPathology practiceProstate
2019
Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology
Bera K, Schalper KA, Rimm DL, Velcheti V, Madabhushi A. Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology. Nature Reviews Clinical Oncology 2019, 16: 703-715. PMID: 31399699, PMCID: PMC6880861, DOI: 10.1038/s41571-019-0252-y.Peer-Reviewed Original ResearchMeSH KeywordsArtificial IntelligenceHumansMedical OncologyNeoplasmsPathology, ClinicalPrecision MedicineConceptsArtificial intelligenceMachine learning toolsDigital pathologyUse of AIDeep neural networksLearning toolsStained tissue specimensWhole slide imagesFeature-based methodologyNeural networkIntelligencePotential future opportunitiesMorphometric phenotypesNetworkValidation datasetComputational approachToolMiningEnormous divergenceDatasetImagesPrecision oncologyFrameworkComplex processFuture opportunities
2005
Detection of malignancy in cytology specimens using spectral–spatial analysis
Angeletti C, Harvey NR, Khomitch V, Fischer AH, Levenson RM, Rimm DL. Detection of malignancy in cytology specimens using spectral–spatial analysis. Laboratory Investigation 2005, 85: 1555-1564. PMID: 16200074, DOI: 10.1038/labinvest.3700357.Peer-Reviewed Original Research